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An Improved Neighbor Selection Algorithm in Collaborative Filtering
Taek-Hun KIM
Sung-Bong YANG
Publication
IEICE TRANSACTIONS on Information and Systems Vol.E88-D No.5 pp.1072-1076
Publication Date: 2005/05/01
Online ISSN:
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Contents Technology and Web Information Systems
Keyword:
recommender system,
neighbor selection algorithm,
collaborative filtering,
Full Text: PDF(121.7KB)
Summary:
Nowadays, customers spend much time and effort in finding the best suitable goods since more and more information is placed on-line. To save their time and effort in searching the goods they want, a customized recommender system is required. In this paper we present an improved neighbor selection algorithm that exploits a graph approach. The graph approach allows us to exploit the transitivity of similarities. The algorithm searches more efficiently for set of influential customers with respect to a given customer. We compare the proposed recommendation algorithm with other neighbor selection methods. The experimental results show that the proposed algorithm outperforms other methods.
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